Our ebook, AI in Customer Analytics: Tapping Your Data for Success, takes a deep dive into the many ways that companies can put their AI to work for better customer success.
This whitepaper explores the practical applications of predictive analytics within retail and how it can be used to deliver a smarter shopping experience.
Using the CRISP-DM framework can help make this process much simpler and give you a clear structure and set of criteria that you can use for your assessment. We have prepared a short guide explaining how best to use CRISP DM as a framework for evaluating data mining tools.
In this ebook, you’ll see how business leaders are leveraging AI to decrease machine downtime, improve demand forecasts, and accelerate supply chain logistics. You’ll discover that AI isn’t an intimidating technology, but rather a practical tool to grow your business and change the world.
This white paper is designed to explain predictive analytics, followed by a look at how it can impact activity at the highest levels of institutional management. We provide examples of how predictive analytics has been used at a variety of institutions, including a review of its potential pitfalls and benefits.
The purpose of this paper is to demonstrate the benefits of using R and SPSS together, rather than simply trying to go it alone with R. With SPSS software, R users get access to superior data management, a point-and-click interface, presentation-quality output and improved scalability.
This white paper presents a number of typical, real world examples of predictive analytics and shows how it can be used to address key business issues, with the aim of illustrating practical ways in which analytical capabilities can be deployed in a range of different organisations.
Our report, The Business Value of MLOps by Thomas Davenport, highlights some of the most impactful benefits of MLOps tools and processes for different types of organisations. It is based on interviews with MLOps user companies and several MLOps experts.
This white paper discusses survey research by breaking it up into a seven step process — and clearly detailing how you maximize your efforts every step of the way. At each stage, it also shows how IBM SPSS predictive analytics technology can improve your results.
This free white paper presents some points you should consider if you use, or plan to use, a spreadsheet to perform statistical analysis. It also describes an alternative that in many cases will be more suitable.
Download this ebook to learn how DataRobot and Intel® work together so that enterprises can quickly train large datasets and build production-ready machine learning models, and more.
If you’re familiar with programming languages such as Python or R then you can use them to extend the functionality of SPSS, automate more processes and make your jobs more stable and robust. This white paper tells you how to develop such IBM SPSS Statistics extension commands.